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| EKO2002 | Econometrics - II | 3+0+0 | ECTS:7 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of ECONOMETRICS | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Arş. Gör. Serkan SAMUT | | Co-Lecturer | PROF. DR. RAHMİ YAMAK | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to teach testing and correcting specification errors appearing when an econometrics model is established, to show how to analyze relationships among economics variables using specific econometric models. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | apply statistical methods for solving economics problems. | 2,3 | 1, | | LO - 2 : | determine and empirically solve the economics problems. | 2,3 | 1, | | LO - 3 : | model, estimate and interpret the economics problems. | 2,3 | 1, | | LO - 4 : | analyse by using statistics, mathematics and economics. | 2,3 | 1, | | LO - 5 : | have findings for future. | 2,3 | 1, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Detection, Effects and Correction of Heteroscedasticity, Detection, Effects and Correction of Autocorrelation, Distributed Lag Models, Simultaneous-equation Models, Stationarity Tests, Co-integration Tests, Causality Tests and Error Correction Model.
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Tests for Heteroscedasticity
| | | Week 2 | Weighted Ordinary Least Square
| | | Week 3 | Autocorrelation
| | | Week 4 | Cochrane-Orcutt Methods
| | | Week 5 | Koyck Model
| | | Week 6 | Almon Model
| | | Week 7 | Recursive Equation Systems and Seemingly Unrelated Regressions
| | | Week 8 | Indirect OLS
| | | Week 9 | Mid-term exam
| | | Week 10 | 2SLS and 3SLS
| | | Week 11 | Unit-Root Tests
| | | Week 12 | Co-Integration Tests
| | | Week 13 | Causality Tests
| | | Week 14 | Vector Autoregressions
| | | Week 15 | Box-Jenkins Models
| | | Week 16 | End-of-term exam
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| 1 | Köseoğlu, M. , Yamak, R. , 2004, Uygulamalı İstatistik ve Ekonometri, Aksakal Kitabevi, Trabzon | | | |
| 1 | Gujarati, D. , 1999; Temel Ekonometri (Çev. : Şenesen, Ü. , Şenesen, Gülay G. ) , İstanbul | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 10/04/2024 | 1 | 50 | | End-of-term exam | 16 | 01/06/2024 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 5 | 14 | 70 | | Arasınav için hazırlık | 11 | 2 | 22 | | Arasınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 24 | 3 | 72 | | Dönem sonu sınavı | 2 | 1 | 2 | | Diğer 1 | 1 | 1 | 1 | | Total work load | | | 210 |
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